Automatic fault diagnosis can provide an answer to the time, cost and skills issues that hinder efforts to detect and deal with vibration problems before they become critical. Lee McFarlane, of AVT Reliability®, explains how.
Vibration analysis should form a central part of any reliability programme, yet it is still considered a ‘black art’ in many industries – and a costly and time-consuming one at that.
There’s good reason for this. The potential faults indicated by excess vibration are numerous and can indicate anything from easily remedied misalignment or the need to replace rolling bearing, to complex issues such as rotor bar conditions or soft foot.
A dedicated on-site vibration engineer who can analyse data and make informed decisions that prevent fault conditions developing into equipment failure, is a highly valuable asset to any reliability team. However, financial constraints can mean that to have such expertise on the staff roster often remains the preserve of bigger industries such as oil and gas or petrochemicals.
For companies where unscheduled downtime would be equally disastrous, but which have tight financial margins that simply don’t stretch to having a qualified vibration analyst permanently on site, this can be a problem, especially as outsourcing vibration analysis to external specialists can prove almost as costly.
The answer could lie in automatic fault diagnosis – an algorithm-based approach to vibration monitoring and analysis which offers both simplicity of use and cost-efficiency. An example of this is the Machine Sentry®.
A tri-axial sensor is attached to a piece of rotating equipment and is connected to the software via a handheld android phone or tablet using standard Bluetooth wireless technology.
Continuous monitoring and visibility across three axes mean there’s no risk of fault conditions going undetected. And replacing a traditional wired accelerometer with wireless technology means that data can be collected from a distance of more than 50m – making it safe and easy to collect even from large, moving or hard-to-access assets.
But the primary feature of the technology is its Automatic Diagnostic Assistant (ADATM). This algorithm, built upon a long heritage of vibration analysis, is able to analyse the data the instant it is collected and suggest what action maintenance engineers should take to confirm precisely what the problem is, and remedy it.
Informed by thousands of hours of vibration data coupled with the extensive field experience of vibration specialists, ADATM has the ability to automatically detect and report on 22 common conditions which have the potential to reduce machine reliability or, at worst, bring production to a standstill.
- Unbalance (couple, static, dynamic and overhung)
- Bent shaft
- Parallel, angular, or complex misalignment
- Cocked bearing
- Structural or rotating looseness
- Blade or vane pass issues
- Soft foot
- Lack of lubrication
- Gear misalignment
- Gear backlash / eccentricity
- Gear tooth broken
- Gear tooth wear
- Bearing stage 2, 3, or 4
ADATM will either pinpoint the single most likely problem, or present up to four potential points of failure, ranked in order of greatest likelihood, and outline the next steps to take. This could be anything from cleaning and rebalancing a rotating component, to structural looseness.
A simple traffic light system, where green means no issue is detected, rising to amber and red where problems are identified, bridges the skills gap so any maintenance engineer can use automatic fault diagnosis to maximise plant reliability.
Budget implications are an obvious concern for any responsible reliability manager but it’s worth considering the immediate cost offsets offered by algorithms like ADATM:
- It takes two years of training and experience to develop a vibration analyst
- It takes roughly two hours for an experienced vibration analyst to evaluate data and make an informed decision
- There is no need to outsource data analysis
- Proactive, preventive maintenance leads to long-term savings
It’s calculated that for every £1 spent on automatic fault diagnosis technology, at least £5 is saved in terms of time, expertise and hardware and software costs. Over a 3 year period there is an estimated increased uptime of 33%, parts are reduced by 23% and labour costs reduced 16%. For a company with a close eye on reliability and the bottom line, investing in this technology is surely a no-brainer.